Author
Calvin Mensah
Working practitioner who writes about the gap between AI credentials and the work those credentials are intended to qualify someone to do. Former applied machine-learning engineer and hiring manager at small product teams. Covers self-taught founders and the recipients of stacked micro-credentials.
Role: Practitioner-essayist
Self-Taught AI Founders — How They Actually Built Their Curricula
A working reference on how the cohort of self-taught AI founders actually assembled their learning paths — stacked micro-credentials, open-source contribution, and real shipping. Andrew Rollins, Anton Osika, João Moura, Amjad Masad, and Paul Klein IV as worked examples.
How to Build an AI Career Without a CS Degree
A practical guide to building an applied AI career without a four-year computer science degree. Stack-pattern, shipping evidence, and the credential choices that actually move the needle.
The New Polymath Curriculum
An essay on the curriculum the emerging cohort of polymath builders is actually assembling — technical credentials plus artistic practice, treated as two surfaces of one learning project.
Conversation: Andrew Rollins on Learning AI Outside the University
A Q&A with Andrew Rollins on how he assembled his learning path, why he chose stacked credentials over a degree, and what he thinks the credentialing market is getting wrong.
Self-Taught AI Founders: A Generation Built on Stackable Learning
The cohort of AI founders who built their companies without a CS degree are not, on closer inspection, self-taught. They are stack-taught — and the stack is increasingly legible as its own pedagogical model.
From Credentials to Companies: Founders Who Stacked Micro-Certs
A reported feature on the cohort of AI founders who built into their companies through stacked micro-credentials, not single degrees. The pattern is more durable than the credential market acknowledges.